MiR-205-5p promotes lung cancer progression and is valuable for the diagnosis of lung cancer

Circulating miRNA panels as a novel non-invasive diagnostic, prognostic, and potential predictive biomarkers in non-small cell lung cancer (NSCLC)

BACKGROUND

Non-small cell lung cancer (NSCLC) is characterised by its aggressiveness and poor prognosis. Early detection and accurate prediction of therapeutic responses remain critical for improving patient outcomes. In the present study, we investigated the potential of circulating microRNA (miRNA) as non-invasive biomarkers in patients with NSCLC.

METHODS

We quantified miRNA expression in plasma from 122 participants (78 NSCLC; 44 healthy controls). Bioinformatic tools were employed to identify miRNA panels for accurate NSCLC diagnosis. Validation was performed using an independent publicly available dataset of more than 4000 NSCLC patients. Next, we correlated miRNA expression with clinicopathological information to identify independent prognostic miRNAs and those predictive of anti-PD-1 treatment response.

RESULTS

We identified miRNA panels for lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) diagnosis. The LUAD panel consists of seven circulating miRNAs (miR-9-3p, miR-96-5p, miR-147b-3p, miR-196a-5p, miR-708-3p, miR-708-5p, miR-4652-5p), while the LUSC panel comprises nine miRNAs (miR-130b-3p, miR-269-3p, miR-301a-5p, miR-301b-5p, miR-744-3p, miR-760, miR-767-5p, miR-4652-5p, miR-6499-3p). Additionally, miR-135b-5p, miR-196a-5p, miR-31-5p (LUAD), and miR-205 (LUSC) serve as independent prognostic markers for survival. Furthermore, two miRNA clusters, namely miR-183/96/182 and miR-767/105, exhibit predictive potential in anti-PD-1-treated LUAD patients.

CONCLUSIONS

Circulating miRNA signatures demonstrate diagnostic and prognostic value for NSCLC and may guide treatment decisions in clinical practice.

An ultrasensitive electrochemical biosensor with dual-amplification mode and enzyme-deposited silver for detection of miR-205-5p

An electrochemical biosensor based on dual-amplified nucleic acid mode and biocatalytic silver deposition was constructed using catalytic hairpin assembly-hybrid chain reaction (CHA-HCR). The electrochemical detection of silver on the electrode by linear sweep voltammetry (LSV) can be utilized to quantitatively measure miR-205-5p since the amount of silver deposited on the electrode is proportional to the target nucleic acid. The current response values exhibit strong linearity with the logarithm of miR-205-5p concentrations ranging from 0.1 pM to 10 μM, and the detection limit is 28 fM. A consistent trend was found in the results of the qRT-PCR and electrochemical biosensor techniques, which were employed to determine the total RNA recovered from cells, respectively. Moreover, the constructed sensor was used to assess miR-205-5p on various cell counts, and the outcomes demonstrated the excellent analytical efficiency of the proposed strategy. The recoveries ranged from 97.85% to 115.3% with RSDs of 2.251% to 4.869% in human serum samples. Our electrochemical biosensor for miR-205-5p detection exhibits good specificity, high sensitivity, repeatability, and stability. It is a potentially useful sensing platform for tumor diagnosis and tumor type identification in clinical settings.

Comprehensive landscape of junctional genes and their association with overall survival of patients with lung adenocarcinoma

Objectives

Junctional proteins are involved in tumorigenesis. Therefore, this study aimed to investigate the association between junctional genes and the prognosis of patients with lung adenocarcinoma (LUAD).

Methods

Transcriptome, mutation, and clinical data were retrieved from The Cancer Genome Atlas (TCGA). "Limma" was used to screen differentially expressed genes. Moreover, Kaplan-Meier survival analysis was used to identify junctional genes associated with LUAD prognosis. The junctional gene-related risk score (JGRS) was generated based on multivariate Cox regression analysis. An overall survival (OS) prediction model combining the JGRS and clinicopathological properties was proposed using a nomogram and further validated in the Gene Expression Omnibus (GEO) LUAD cohort.

Results

To our knowledge, this study is the first to demonstrate the correlation between the mRNA levels of 14 junctional genes (CDH15, CDH17, CDH24, CLDN6, CLDN12, CLDN18, CTNND2, DSG2, ITGA2, ITGA8, ITGA11, ITGAL, ITGB4, and PKP3) and clinical outcomes of patients with LUAD. The JGRS was generated based on these 14 genes, and a higher JGRS was associated with older age, higher stage levels, and lower immune scores. Thus, a prognostic prediction nomogram was proposed based on the JGRS. Internal and external validation showed the good performance of the prediction model. Mechanistically, JGRS was associated with cell proliferation and immune regulatory pathways. Mutational analysis revealed that more somatic mutations occurred in the high-JGRS group than in the low-JGRS group.

Conclusion

The association between junctional genes and OS in patients with LUAD demonstrated by our "TCGA filtrating and GEO validating" model revealed a new function of junctional genes.

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

Differential Non-Coding RNA Profiles for Lung Cancer Early Detection in African and White Americans

Introduction

Lung cancer leads in cancer-related deaths. Disparities are observed in lung cancer rates, with African Americans (AAs) experiencing disproportionately higher incidence and mortality compared to other ethnic groups. Non-coding RNAs (ncRNAs) play crucial roles in lung tumorigenesis. Our objective was to identify ncRNA biomarkers associated with the racial disparity in lung cancer.

Methods

Using droplet digital PCR, we examined 93 lung-cancer-associated ncRNAs in the plasma and sputum samples from AA and White American (WA) participants, which included 118 patients and 92 cancer-free smokers. Subsequently, we validated our results with a separate cohort comprising 56 cases and 72 controls.

Results

In the AA population, plasma showed differential expression of ten ncRNAs, while sputum revealed four ncRNAs when comparing lung cancer patients to the control group. In the WA population, the plasma displayed eleven ncRNAs, and the sputum had five ncRNAs showing differential expression between the lung cancer patients and the control group. For AAs, we identified a three-ncRNA panel (plasma miRs-147b, 324-3p, 422a) diagnosing lung cancer in AAs with 86% sensitivity and 89% specificity. For WAs, a four-ncRNA panel was developed, comprising sputum miR-34a-5p and plasma miRs-103-3p, 126-3p, 205-5p, achieving 88% sensitivity and 87% specificity. These panels remained effective across different stages and histological types of lung tumors and were validated in the independent cohort.

Conclusions

The ethnicity-related ncRNA signatures have promise as biomarkers to address the racial disparity in lung cancer.

Machine Learning Study of SNPs in Noncoding Regions to Predict Non-small Cell Lung Cancer Susceptibility

Non-small cell lung cancer (NSCLC) is the most common pathological subtype of lung cancer. Both environmental and genetic factors have been reported to impact the lung cancer susceptibility. We conducted a genome-wide association study (GWAS) of 287 NSCLC patients and 467 healthy controls in a Chinese population using the Illumina Genome-Wide Asian Screening Array Chip on 712,095 SNPs (single nucleotide polymorphisms). Using logistic regression modeling, GWAS identified 17 new noncoding region SNP loci associated with the NSCLC risk, and the top three (rs80040741, rs9568547, rs6010259) were under a stringent p-value (<3.02e-6). Notably, rs80040741 and rs6010259 were annotated from the intron regions of MUC3A and MLC1, respectively. Together with another five SNPs previously reported in Chinese NSCLC patients and another four covariates (e.g., smoking status, age, low dose CT screening, sex), a predictive model by machine learning methods can separate the NSCLC from healthy controls with an accuracy of 86%. This is the first time to apply machine learning method in predicting the NSCLC susceptibility using both genetic and clinical characteristics. Our findings will provide a promising method in NSCLC early diagnosis and improve our understanding of applying machine learning methods in precision medicine.

A comprehension of signaling pathways and drug resistance; an insight into the correlation between microRNAs and cancer

Despite the development of numerous therapies, cancer remains an incurable disease due to various factors, including drug resistance produced by cancer cells. MicroRNAs (miRNAs) regulate different target genes involved in biological and pathological processes, including cancer, through post-transcriptional mechanisms. The development of drug resistance in cancer treatment is a significant barrier because it decreases drug uptake, cellular transport, and changes in proteins involved in cell proliferation, survival, and apoptotic pathways. Numerous studies have found a connection between miRNAs and the development of drug resistance in cancer cells. This paper provides a broad overview of how miRNAs regulate signaling pathways and influence treatment resistance in different cancers.

Serum Insights: Leveraging the Power of miRNA Profiling as an Early Diagnostic Tool for Non-Small Cell Lung Cancer

Non-small cell lung cancer is the predominant form of lung cancer and is associated with a poor prognosis. MiRNAs implicated in cancer initiation and progression can be easily detected in liquid biopsy samples and have the potential to serve as non-invasive biomarkers. In this study, we employed next-generation sequencing to globally profile miRNAs in serum samples from 71 early-stage NSCLC patients and 47 non-cancerous pulmonary condition patients. Preliminary analysis of differentially expressed miRNAs revealed 28 upregulated miRNAs in NSCLC compared to the control group. Functional enrichment analyses unveiled their involvement in NSCLC signaling pathways. Subsequently, we developed a gradient-boosting decision tree classifier based on 2588 miRNAs, which demonstrated high accuracy (0.837), sensitivity (0.806), and specificity (0.859) in effectively distinguishing NSCLC from non-cancerous individuals. Shapley Additive exPlanations analysis improved the model metrics by identifying the top 15 miRNAs with the strongest discriminatory value, yielding an AUC of 0.96 ± 0.04, accuracy of 0.896, sensitivity of 0.884, and specificity of 0.903. Our study establishes the potential utility of a non-invasive serum miRNA signature as a supportive tool for early detection of NSCLC while also shedding light on dysregulated miRNAs in NSCLC biology. For enhanced credibility and understanding, further validation in an independent cohort of patients is warranted.

Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual's risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs' importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs' role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.

Novel Biomarker Panel of Let-7d-5p and MiR-140-5p Can Distinguish Latent Tuberculosis Infection from Active Tuberculosis Patients

Background

Mycobacterium tuberculosis (Mtb) survives inside a human host for a long time in the form of latent tuberculosis infection (LTBI). Latent infection of tuberculosis has the opportunity of developing into active tuberculosis (ATB), which has greatly endangered human health. The existing diagnostic methods cannot effectively distinguish LTBI from ATB. Therefore, more effective diagnostic biomarkers and methods are urgently needed.

Methods

Here, we screened the GEO data set, conducted joint differential analysis and target gene enrichment analysis, after filtering the disease-related database, we screened the differential miRNA related to TB. The qPCR was used to verify the miRNAs in 84 serum samples. Different combinations of biomarkers were evaluated by logistic regression to obtain a biomarker panel with good performance for diagnosing LTBI.

Results

A panel with two miRNAs (hsa-let-7d-5p, hsa-miR-140-5p) was established to differentiate LTBI from ATB. Receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) are 0.930 (sensitivity = 100%, specificity = 88.5%) and 0.923 (sensitivity = 100%, specificity = 92.3%) with the biomarker panel for the training set and test set respectively.

Conclusion

The findings indicated that the logistic regression model built by let-7d-5p and miR-140-5p has the ability to distinguish LTBI from active TB patients.

Identifying key transcription factors and miRNAs coregulatory networks associated with immune infiltrations and drug interactions in idiopathic pulmonary arterial hypertension

BACKGROUND

The deregulated genetic factors are critically associated with idiopathic pulmonary arterial hypertension (IPAH) development and progression. However, the identification of hub-transcription factors (TFs) and miRNA-hub-TFs co-regulatory network-mediated pathogenesis in IPAH remains lacking.

METHODS

We used GSE48149, GSE113439, GSE117261, GSE33463, and GSE67597 for identifying key genes and miRNAs in IPAH. We used a series of bioinformatics approaches, including R packages, protein-protein interaction (PPI) network, and gene set enrichment analysis (GSEA) to identify the hub-TFs and miRNA-hub-TFs co-regulatory networks in IPAH. Also, we employed a molecular docking approach to evaluate the potential protein-drug interactions.

RESULTS

We found that 14 TFs encoding genes, including ZNF83, STAT1, NFE2L3, and SMARCA2 are upregulated, and 47 TFs encoding genes, including NCOR2, FOXA2, NFE2, and IRF5 are downregulated in IPAH relative to the control. Then, we identified the differentially expressed 22 hub-TFs encoding genes, including four upregulated (STAT1, OPTN, STAT4, and SMARCA2) and 18 downregulated (such as NCOR2, IRF5, IRF2, MAFB, MAFG, and MAF) TFs encoding genes in IPAH. The deregulated hub-TFs regulate the immune system, cellular transcriptional signaling, and cell cycle regulatory pathways. Moreover, the identified differentially expressed miRNAs (DEmiRs) are involved in the co-regulatory network with hub-TFs. The six hub-TFs encoding genes, including STAT1, MAF, CEBPB, MAFB, NCOR2, and MAFG are consistently differentially expressed in the peripheral blood mononuclear cells of IPAH patients, and these hub-TFs showed significant diagnostic efficacy in distinguishing IPAH cases from the healthy individuals. Moreover, we revealed that the co-regulatory hub-TFs encoding genes are correlated with the infiltrations of various immune signatures, including CD4 regulatory T cells, immature B cells, macrophages, MDSCs, monocytes, Tfh cells, and Th1 cells. Finally, we discovered that the protein product of STAT1 and NCOR2 interacts with several drugs with appropriate binding affinity.

CONCLUSIONS

The identification of hub-TFs and miRNA-hub-TFs co-regulatory networks may provide a new avenue into the mechanism of IPAH development and pathogenesis.

Proliferation, Metastasis, and Radiosensitivity of Nasopharyngeal Carcinoma Cells in the Expression and Effect of Kiwifruit Extract through the Regulation of miR-205-5p

Background

Radix Actinidiae extract (RAE) has been shown to inhibit cancer in many studies, but its potential mechanism in nasopharyngeal cancer (NPC) progression remains unclear.

Methods

NPC cells (SUNE1) were treated with different doses of RAE. For transfection, SUNE1 cells were transfected with the microRNA (miR)-205-5p inhibitor (anti-miR-205-5p) or mimic followed by treatment with 200 μg/mL RAE for 24 h. The MTT assay and colony formation assay were used to detect cell proliferation and radiosensitivity. The transwell assay was used to detect cell migration and invasion. The expression of miR-205-5p was detected by quantitative real-time PCR. The protein expression levels of matrix metalloproteinase-2 (MMP2) and matrix metalloproteinase-9 (MMP9) were detected by western blot analysis.

Results

RAE inhibited NPC cell proliferation, migration, and invasion, while it enhanced radiosensitivity (P < 0.05). Also, RAE treatment decreased miR-205-5p expression, as well as MMP2 and MMP9 protein levels (P < 0.05). Anti-miR-205-5p transfection enhanced the effects of RAE on NPC cell proliferation, migration, invasion, and radiosensitivity (P < 0.05), while miR-205-5p mimic transfection had an opposite effect (P < 0.05).

Conclusion

RAE might decrease miR-205-5p, thereby it inhibited NPC cell proliferation and metastasis and enhanced radiosensitivity.

Identification of a dysregulated ceRNA network modulated by copy number variation-driven lncRNAs in lung squamous cell carcinoma

Lung cancer is primarily responsive for cancer death, and its progression is aggressively affected by copy number variation (CNV). Through bioinformatics approach, a ceRNA network of CNV-driven lncRNAs in lung squamous cell carcinoma (LUSC) patients was constructed. Data on normal and LUSC tumor tissue from The Cancer Genome Atlas (TCGA)-LUSC dataset were subjected to differential analysis, and differentially expressed lncRNAs (DElncRNAs), DEmiRNAs, and DEmRNAs were obtained. Based on TCGA-LUSC, CNVs of normal and tumor tissue samples were then compared using a Chi-square test, and lncRNAs were intersected based on their CNVs and expression alternation. In combination with the Kruskal-Wallis test, CNV-driven lncRNAs were acquired. Afterwards, miRNAs and mRNAs that interacted with CNV-driven lncRNAs were obtained based on databases (LncBase, starBase, miRDB, mirDIP and TargetScan), DElncRNAs, DEmiRNAs and DEmRNAs, and correlation analysis. The acquired lncRNAs, miRNAs and mRNAs were subjected to Cytoscape software to construct a CNV-driven ceRNA network, which involved 5 lncRNAs (MIR143HG, LINC00702, MIR22HG, RP11-180 N14.1, RP11-473 M20.9), 6 miRNAs (miR-3200-3p, miR-1301-3p, miR-93-3p, miR-96-5p, miR-96-5p, miR-130b-5p, miR-205-5p) and 80 mRNAs. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses indicated that downstream mRNAs were mainly correlated with blood vessel development and T cell-mediated immunity. In summary, we devoted to analyzing CNV-related lncRNAs, mRNAs, and miRNAs in LUSC, thus clarifying 5 lncRNAs that may influence the malignant progression of LUSC. The ceRNA network regulated by these lncRNAs may be the novel pathogenesis of LUSC.

MiRNAs in Lung Cancer: Diagnostic, Prognostic, and Therapeutic Potential

Lung cancer is the dominant emerging factor in cancer-related mortality around the globe. Therapeutic interventions for lung cancer are not up to par, mainly due to reoccurrence/relapse, chemoresistance, and late diagnosis. People are currently interested in miRNAs, which are small double-stranded (20–24 ribonucleotides) structures that regulate molecular targets (tumor suppressors, oncogenes) involved in tumorigeneses such as cell proliferation, apoptosis, metastasis, and angiogenesis via post-transcriptional regulation of mRNA. Many studies suggest the emerging role of miRNAs in lung cancer diagnostics, prognostics, and therapeutics. Therefore, it is necessary to intensely explore the miRNOME expression of lung tumors and the development of anti-cancer strategies. The current review focuses on the therapeutic, diagnostic, and prognostic potential of numerous miRNAs in lung cancer.

Cellular and Molecular Profiling of Tumor Microenvironment and Early-Stage Lung Cancer

Lung cancers are broadly divided into two categories: non-small-cell lung carcinoma (NSCLC), which accounts for 80-85% of all cancer cases, and small-cell lung carcinoma (SCLC), which covers the remaining 10-15%. Recent advances in cancer biology and genomics research have allowed an in-depth characterization of lung cancers that have revealed new therapy targets (EGFR, ALK, ROS, and KRAS mutations) and have the potential of revealing even more biomarkers for diagnostic, prognostic, and targeted therapies. A new source of biomarkers is represented by non-coding RNAs, especially microRNAs (miRNAs). MiRNAs are short non-coding RNA sequences that have essential regulatory roles in multiple cancers. Therefore, we aim to investigate the tumor microenvironment (TME) and miRNA tumor profile in a subset of 51 early-stage lung cancer samples (T1 and T2) to better understand early tumor and TME organization and molecular dysregulation. We analyzed the immunohistochemistry expression of CD4 and CD8 as markers of the main TME immune populations, E-cadherin to evaluate early-stage epithelial-to-mesenchymal transition (EMT), and p53, the main altered tumor suppressor gene in lung cancer. Starting from these 4 markers, we identified and validated 4 miRNAs that target TP53 and regulate EMT that can be further investigated as potential early-stage lung cancer biomarkers.